A variety of program evaluation designs are available to assess the impact of disease or care management programs, which can make it difficult to compare outcomes of different interventions. The need to compare programs has resulted in consideration of standardizing evaluations of disease management programs; however, recommendations on the conduct of such evaluations have not been widely adopted. The purpose of this article is to examine the consistency of study characteristics of disease management peer reviewed evaluations over a 3-year period (1 January 2004-28 February 2007) and to suggest questions that must be answered to ensure basic transparency of methods and metrics.
Study designs vary considerably among the current literature on evaluations of disease management interventions involving US health plans (25 studies). The mechanism for defining the intervention populations were not consistent, even among interventions focused on a single disease, and evaluations employed both administrative and clinical data. The current literature included both randomized (n = 10) and non-randomized studies (n = 15). The referent population varied among the non-randomized studies, and included data from the pre-intervention period and both concurrent and historical control groups. The outcome metrics used in the evaluations included mortality and readmission rates, as well as time to readmission and various cost parameters. The majority of reviewed studies corrected for the confounding variables of age and sex, and a high proportion corrected for a range of other confounding factors.
In conclusion, the evaluations of disease management programs in the literature cannot be considered standardized. To increase the transparency and validity of disease management intervention evaluations, we recommend consideration of five basic questions regarding intervention descriptions, intervention population, referent population, outcomes metrics, and confounding variables. Standardization on such basic parameters is a necessary step towards being able to assess the quality and validity of evaluations. Such standardization is essential for comparing the effectiveness of alternative programs, and to enable data-driven value-based purchasing decisions.